In recent decades, many climate manipulation experiments have investigated biosphere responses to global change. These experiments typically examined effects of elevated atmospheric CO2, warming or drought (driver variables) on ecosystem processes such as the carbon and water cycle (response variables). Because experiments are inevitably constrained in the number of driver variables tested simultaneously, time and space, a key question is how results are scaled up to predict net ecosystem responses. Here, we argue that a wealth of information is hidden in the combination of results from several global change experiments and multi-year time series. Our aim is to search for general patterns that cannot be evidenced by single experiments or shorter time series.
Results/Conclusions
We find that there might be a general trend for the magnitude of the responses to global change drivers to decline with higher-order interactions, longer time periods and larger spatial scales. This means that on average, both positive and negative global change impacts on the biosphere might be dampened more than previously assumed. Further, by looking at long time series of the NPP response to elevated CO2, we find important, not previously documented interactions between the CO2 effect and the timing of rainfall. For example, more rain in summer can increase the net CO2 response at dry sites, while at wetter sites, more rain can decrease the CO2 response.